Awesome Generative UI - AI-Powered User Interface Generation Resources

Generative UI: A rich, custom, visual interactive user experience for any prompt

Yaniv Leviathan, Google Fellow, Dani Valevski, Senior Staff Software Engineer, Vishnu Natchu, Principal Engineer, and Yossi Matias, Vice President & Head of Google Research

Generative UI: The AI agent is the front end

In a new model for user interfaces, agents paint the screen with interactive UI components on demand. Let’s take a look.

Why Generative UI Is the New Frontier for Business Software

In an era where AI constructs UIs on the fly, discover how SAP is tapping generative UI to reimagine how works gets done.

Beautiful UI — Crafted primitives for AI-native interfaces

A small library of extremely crafted, copy-paste components for chat agents, thinking states, human-in-the-loop approvals, and everything agents need to talk to humans beautifully.

Reverse-engineering Claude's generative UI - then building it for the terminal

Extracting Anthropic's design system from a conversation export and rebuilding generative UI for the terminal.

Create | Diffuse

You can generate interfaces or features easily using AI. Diffuse provides a skill to use with LLMs. Claude usage example:

Popmelt — Design copilots for AI agents

Our Taste models encode design expertise and philosophy, giving AI agents instant access to a curated catalog of aesthetic knowledge. Unlike traditional templates and design systems, our imprints are AI-native and guided by universal principles. This means agents can apply them to any interface scenario, not just predefined layouts and elements. They're also customizable and extensible, letting you build quickly without falling into the cookie-cutter UI library trap.

Steven Vandevelde (@tokono.ma)

So cool that I can just generate this interface without interfering with the rest of the software.

Anthropic experiments with real-time UI generation on Claude

What do we know so far? "Imagine with Claude" will be released as a temporary demo for certain plans (only Max?). Users will be interacting with a classic desktop UI where windows and apps are managed by the AI itself.

Generative Agents: Interactive Simulacra of Human Behavior

Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. In this paper, we introduce generative agents--computational software agents that simulate believable human behavior. Generative agents wake up, cook breakfast, and head to work; artists paint, while authors write; they form opinions, notice each other, and initiate conversations; they remember and reflect on days past as they plan the next day. To enable generative agents, we describe an architecture that extends a large language model to store a complete record of the agent's experiences using natural language, synthesize those memories over time into higher-level reflections, and retrieve them dynamically to plan behavior. We instantiate generative agents to populate an interactive sandbox environment inspired by The Sims, where end users can interact with a small town of twenty five agents using natural language. In an evaluation, these generative agents produce believable individual and emergent social behaviors: for example, starting with only a single user-specified notion that one agent wants to throw a Valentine's Day party, the agents autonomously spread invitations to the party over the next two days, make new acquaintances, ask each other out on dates to the party, and coordinate to show up for the party together at the right time. We demonstrate through ablation that the components of our agent architecture--observation, planning, and reflection--each contribute critically to the believability of agent behavior. By fusing large language models with computational, interactive agents, this work introduces architectural and interaction patterns for enabling believable simulations of human behavior.

MCP-UI | Interactive UI for MCP

Interactive UI for MCP - Build rich, dynamic interfaces with MCP-UI

Macaron-A2UI: A Model for Generative UI in Personal Agents

As personal agents evolve to handle complex, user-centric tasks, static plain-text chat is rapidly becoming a bottleneck. Generative UI emerges as the necessary new interface layer, dynamically synthesizing the right controls, options, and state from the interaction context in real time. We present Macaron-A2UI, a model for Generative UI in personal agents. Our goal is to move beyond text-only interaction by enabling agents to generate natural language together with lightweight, executable UI actions for information collection, preference refinement, confirmation, and multi-goal organization. We build a large-scale Generative UI corpus from heterogeneous dialogue sources, introduce A2UI-Bench for controlled evaluation, and train 30B, 235B and 754B models with parameter-efficient LoRA-based supervised fine-tuning followed by reward-driven reinforcement learning. The best Macaron-A2UI model reaches 75.6 overall on A2UI-Bench without explicit schema hints, surpassing the strongest full-schema frontier baseline. We release the models, benchmark, and evaluation protocol to support future work on Generative UI for personal agents.

Unpredictable Black Boxes are Terrible Interfaces

Why generative AI tools can be so difficult to use and how we might improve them

The Myth of the Instant Cake Mix

How to think about creative tooling in the new world of generative AI

Library: Faculty Guide to Generative AI: Detecting AI